Powder flow measurement in additive manufacturing systems

ABSTRACT

A system may include one or more computing devices configured to receive image data representing illuminated powder of a powder stream between a powder delivery device of an additive manufacturing system and a build surface of a component; determine at least one metric associated with the powder stream based on the received image data; determine whether the at least one metric indicates an abnormal state of the at least one metric; and cause the additive manufacturing system to perform at least one action in response to determining that the at least one metric indicates the abnormal state.

This application claims the benefit of U.S. Provisional PatentApplication No. 63/247,571, filed 23 Sep. 2021, the entire contents ofwhich is incorporated herein by reference.

TECHNICAL FIELD

The disclosure relates to additive manufacturing techniques.

BACKGROUND

Additive manufacturing generates three-dimensional structures throughaddition of material layer-by-layer or volume-by-volume to form thestructure, rather than removing material from an existing component togenerate the three-dimensional structure. Additive manufacturing may beadvantageous in many situations, such as rapid prototyping, formingcomponents with complex three-dimensional structures, or the like. Insome examples, additive manufacturing may utilize powdered materials andmay melt or sinter the powdered material together in predeterminedshapes to form the three-dimensional structures.

SUMMARY

In some examples, the disclosure describes an additive manufacturingsystem that includes a powder delivery device configured to direct apowder stream toward a build surface of a component, and a powder flowmonitoring system. The powder delivery device defines a longitudinalaxis oriented toward the build surface. The powder flow monitoringsystem includes an illumination device configured to illuminate at leastsome powder the powder stream between the powder delivery device and thebuild surface; and an imaging device configured to image the illuminatedpowder at an image plane that intersects the longitudinal axis. Theillumination device and the imaging device may be registered to thepowder delivery device in a plane substantially orthogonal to thelongitudinal axis.

In some examples, the disclosure describes a method that includesdirecting, by a powder delivery device, powder stream toward a buildsurface of a component, wherein the powder delivery device defines alongitudinal axis oriented toward the build surface. The method alsoincludes illuminating, by an illumination device of a powder flowmonitoring system, at least some powder of the powder stream between thepowder delivery device and the build surface. The method further mayinclude imaging, by an imaging device of the powder flow monitoringsystem, the illuminated powder at an image plane that intersects thelongitudinal axis, wherein the illumination device and the imagingdevice are registered to the powder delivery device in a planesubstantially orthogonal to the longitudinal axis.

In some examples, the disclosure describes a powder flow monitoringsystem that includes a computing device configured to receive image datarepresenting illuminated powder of a powder stream between a powderdelivery device and a build surface of a component, generate arepresentation of the powder stream based on the image data, and outputthe representation of the powder stream for display at a display device.

In some examples, the disclosure describes a method that includesreceiving, by a computing device, image data representing illuminatedpowder of a powder stream between a powder delivery device and a buildsurface of a component; generating, by the computing device, arepresentation of the powder stream based on the imaged powder; andoutputting, by the computing device, the representation of the powderstream for display at a display device.

In some examples, the disclosure describes a system that includes one ormore computing devices configured to receive image data representingilluminated powder of a powder stream between a powder delivery deviceof an additive manufacturing system and a build surface of a component;determine at least one metric associated with the powder stream based onthe received image data; determine whether the at least one metricindicates an abnormal state of the at least one metric; and cause theadditive manufacturing system to perform at least one action in responseto determining that the at least one metric indicates the abnormalstate.

In some examples, the disclosure describes a method that includesreceiving, by one or more computing devices, image data representingilluminated powder of a powder stream between a powder delivery deviceof an additive manufacturing system and a build surface of a component;determining, by the one or more computing devices, at least one metricassociated with the powder stream based on the received image data;determining, by the one or more computing devices, whether the at leastone metric indicates an abnormal state of the at least one metric; andcausing, by the one or more computing devices, the additivemanufacturing system to perform at least one action in response todetermining that the at least one metric indicates the abnormal state.

The details of one or more examples are set forth in the accompanyingdrawings and the description below. Other features, objects, andadvantages will be apparent from the description and drawings, and fromthe claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a conceptual block diagram illustrating an example additivemanufacturing system that includes a powder flow monitoring systemconfigured to monitor powder flow between a powder delivery device and abuild surface during the additive manufacturing technique.

FIG. 2 is a conceptual and schematic diagram illustrating an examplepowder flow monitoring system configured to monitor powder flow betweena powder delivery device and a build surface during the additivemanufacturing technique.

FIG. 3 is a conceptual diagram illustrating an example of portions of apowder stream imaged by a powder flow monitoring system.

FIG. 4 is an example calibration curve of particle detections versusmass flow.

FIG. 5 is an example graphical user interface screen illustrating heatmaps of mass flow for each of four regions of interest.

FIG. 6 is an example graphical user interface screen illustrating massflow versus time for each of six regions of interest.

FIG. 7A is an example plot of particle detections as a function ofradius and angle for a region of interest.

FIG. 7B is an example plot of particle detections as a function ofradius along a radius of FIG. 7A.

FIG. 8A is an example plot of particle detections in an image planeplotted in polar coordinates.

FIG. 8B is an example plot of number of powder detections versus radialdistance for each of the four quadrants shown in FIG. 9A.

FIG. 9A is an example plot of particle detections in an image planeplotted in polar coordinates for each of two gas flow rates.

FIG. 9B is an example three-dimensional plot of particle detectionsplotted in cartesian coordinates.

FIG. 10A is an example plot of particle detections in an image planeplotted in polar coordinates for each of two gas flow rates.

FIG. 10B is an example three-dimensional plot of particle detectionsplotted in cartesian coordinates.

FIG. 11 is an example plot of particle detections in an image planeplotted in polar coordinates.

FIG. 12 is an example plot of particle detections in an image planeplotted in polar coordinates.

FIG. 13 is an example plot of powder range and standard deviation versustime for each of four image quadrants.

FIGS. 14A and 14B are example heat maps illustrating powder mass flow atdifferent z-axis heights of a powder stream.

FIG. 14C is an image of the powder nozzle used to form the powder flowrepresented in FIGS. 14A and 14B, showing damage in the powder nozzle.

FIG. 15 is a flow diagram illustrating an example technique forcontrolling an additive manufacturing system based on data collectedusing a powder flow monitoring system.

DETAILED DESCRIPTION

The disclosure generally describes techniques and systems for measuringpowder flow between a powder delivery device and a build surface duringa blown powder additive manufacturing technique, such as directed energydeposition. Example powder flow monitoring systems (PFMS) may include anoptical system that includes an illumination device and an imagingdevice. The illumination device and imaging device may work together toimage at least a portion of powder flow between a powder delivery deviceand a build surface. A computing device may analyze the image todetermine a number of powder detections in each image, and may convertthe number of powder detections to powder mass flow or powder mass flowrate, e.g., using a calibration curve. The computing device may beconfigured to output a representation of the powder flow in any one ormore of a variety of formats. For example, the computing device may beconfigured to output a number representing the detections or mass flow(e.g., a numerical mass flow rate in, for example, milligrams per minuteor other appropriate units), a graphical representations of detectionsper unit time or mass flow per unit time, a graphical representation ofdetections or mass flow as a function of position (e.g., axial positionand/or position within the image plane), or the like.

Additionally, or alternatively, the computing device may be configuredto determine one or more powder delivery system characteristics based onthe images. For instance, based on the powder flow distribution, thecomputing device may be configured to identify a damaged powder deliverydevice nozzle, a clog within a powder delivery device nozzle, or thelike.

In some implementations, the computing device may be configured tocontrol the blown powder additive manufacturing technique based on theimage data. For instance, upon detecting a clog, the computing devicemay be configured to cause the powder delivery device to be cleaned,e.g., using a temporary high flow rate of gas though the powder deliverydevice, through mechanical cleaning of the powder delivery device, orthe like. As another example, the computing device may be configured tocompare a measured parameter, such as a measured particle detections, ameasured mass flow rate, a measured detection or mass flow distribution,or the like to a setpoint or set range. Upon determining that themeasured parameter deviates from the setpoint or set range, thecomputing device may control one or more process variables (e.g., massflow of powder from a powder source, process gas flow rate, or the like)and re-measure the measured parameter until computing device determinesthat the measured parameter satisfies the setpoint or the set range.

During blown powder additive manufacturing, a component is built up byadding material to the component in sequential layers. The finalcomponent is composed of a plurality of layers of material. In someblown powder additive manufacturing techniques for forming componentsfrom metals or alloys, an energy source may direct energy at a substrateto form a melt pool. A powder delivery device may deliver a powder tothe melt pool, where at least some of the powder at least partiallymelts and is joined to the melt pool and, thus, substrate.

The resulting layers and final component thus are dependent upon howpowder is captured by the melt pool. For instance, both the fraction ofpowder captured by the melt pool and the shape of the powder stream atthe melt pool (e.g., the focus of the powder stream at the melt pool)affect capture of the powder by the melt pool. Because of the heatgenerated by the energy source a melt pool, and the high velocity of thepowder within the powder stream, monitoring powder flow between thepowder delivery device and the build surface in which the melt pool islocated may be difficult.

In accordance with techniques of this disclosure, a PFMS may include anillumination device, such as a laser, and an imaging device. The laseris configured to illuminate a plane of the powder stream, e.g., a planesubstantially perpendicular to an axis extending between the powderdelivery device and the build surface. The imaging device is configuredto image the illuminated powder. The imaging device may have arelatively high data acquisition speed (e.g., frame rate), such greaterthan 1000 Hz. Because of the velocity of the powder in the powderstream, even such a frame rate may image only a fraction of the powderflowing between the powder delivery device and the build surface.

In some examples, the PFMS also includes a housing configured to enclosethe illumination device and the imaging device. The housing may beconfigured to protect the illumination device and the imaging devicefrom damage due to the harsh conditions to which the PFMS will beexposed during use. For example, the housing may protect theillumination device and the imaging device from powder deflections, maycool the illumination device and the imaging device to remove heat fromthe melt pool and energy source, or the like.

By including a PFMS as described herein and/or using the analysistechniques described herein, understanding and/or control of the powderstream in a blown powder additive manufacturing technique may beimproved. This may facilitate development of blown powder additivemanufacturing techniques for desired components, allow more precisecontrol of a blown powder additive manufacturing technique, or the like.

FIG. 1 is a conceptual block diagram illustrating an example system 10for performing an additive manufacturing technique, such as a blownpowder additive manufacturing technique. System 10 includes a powderflow monitoring system (PFMS) 18 for powder flow between powder deliverydevice 14 and build surface 28 during the blown powder additivemanufacturing technique. In the example illustrated in FIG. 1 , system10 includes a computing device 12, powder delivery device 14, an energydelivery device 16, PFMS 18, and a stage 20. Computing device 12 isoperably connected to powder delivery device 14, energy delivery device16, PFMS 18, and stage 20.

In some examples, stage 20 is movable relative to energy delivery device16 and/or energy delivery device 16 is movable relative to stage 20.Similarly, stage 20 may be movable relative to powder delivery device 14and/or powder delivery device 14 may be movable relative to stage 20.For example, stage 20 may be translatable and/or rotatable along atleast one axis to position component 22 relative to energy deliverydevice 16 and/or powder delivery device 14. Similarly, energy deliverydevice 16 and/or powder delivery device 14 may be translatable and/orrotatable along at least one axis to position energy delivery device 16and/or powder delivery device 14, respectively, relative to component22. Stage 20 may be configured to selectively position and restraincomponent 22 in place relative to stage 20 during manufacturing ofcomponent 22.

Powder delivery device 14 may be configured to deliver powder toselected locations of component 22 being formed via a powder stream 30.Powder delivery device 14 may include one or more nozzles that eachoutput powder. The combined powder defines powder stream 30. In someexamples, powder delivery device 14 includes a single nozzle, which maybe point nozzle, or a single nozzle that is an annular channel. In otherexamples, powder delivery device 14 includes a plurality of nozzles(e.g., three nozzles or four nozzles). Regardless of the number ofnozzles, powder delivery device 14 may output a powder stream that isfocused at a focus plane. As powder delivery device 14 is movable in thez-axis shown in FIG. 1 relative to component 22, the focal plane ofpowder delivery device 14 also may be movable in the z-axis relative tocomponent 22, such that the focus plane may be controlled to besubstantially coincident with build surface 28.

At least some of the powder in powder stream 30 may impact a melt pool32 in component 22. At least some of the powder that impacts melt pool32 may be joined to component 22. In some examples, the powder may besupplied by powder delivery device 14 in powder form, e.g., a powderentrained in a carrier gas flow. In some examples, powder deliverydevice 14 thus may be fluidically coupled to a powder source and a gassource. In some examples, powder delivery device 14 may be mechanicallycoupled or attached to energy delivery device 16 to facilitate deliveryof powder stream 30 and energy 34 for forming melt pool 32 tosubstantially the same location adjacent to component 22.

Energy delivery device 16 may include an energy source, such as a lasersource, an electron beam source, plasma source, or another source ofenergy that may be absorbed by component 22 to form a melt pool 32and/or be absorbed by powder in powder stream 30 to be added tocomponent 22. Example laser sources include a CO laser, a CO₂ laser, aNd:YAG laser, or the like. In some examples, the energy source may beselected to provide energy with a predetermined wavelength or wavelengthspectrum that may be absorbed by component 22 and/or the powder to beadded to component 22 during the additive manufacturing technique.

In some examples, energy delivery device 16 also includes an energydelivery head, which is operatively connected to the energy source. Theenergy delivery head may aim, focus, or direct energy 34 towardpredetermined positions at or adjacent to a surface of component 22during the additive manufacturing technique. As described above, in someexamples, the energy delivery head may be movable in at least onedimension (e.g., translatable and/or rotatable) under control ofcomputing device 12 to direct the energy toward a selected location ator adjacent to a surface of component 22.

In some examples, at least a portion of energy delivery device 16 andpowder delivery device 14 may be combined or attached to each other. Forexample, a deposition head (e.g., deposition head 54 of FIG. 2 ) mayinclude part of powder delivery device 14 (e.g., internal channels andpowder nozzle(s) 56 for forming powder stream 30 and directing powderstream 30 toward build surface 28) and part of energy delivery device 16(e.g., the energy deliver head). As shown in FIG. 1 , in some examples,energy delivery device 16 may be arranged of configured such that energy34 and powder stream 30 both exit from a common deposition head and aredirected toward build surface 28. For instance, energy 34 may passthrough a central channel within the deposition head and exit a centralaperture in the deposition head, while fluidized powder may flow throughinternal channels and powder nozzle(s) 56 for forming powder stream 30and directing powder stream 30 toward build surface 28.

Computing device 12 is configured to control components of system 10 andmay include, for example, a desktop computer, a laptop computer, aworkstation, a server, a mainframe, a cloud computing system, or thelike. Computing device 12 is configured to control operation of system10, including, for example, powder delivery device 14, energy deliverydevice 16, optical system 18, and/or stage 20. Computing device 12 maybe communicatively coupled to powder delivery device 14, energy deliverydevice 16, optical system 18, and/or stage 20using respectivecommunication connections. In some examples, the communicationconnections may include network links, such as Ethernet, ATM, or othernetwork connections. Such connections may be wireless and/or wiredconnections. In other examples, the communication connections mayinclude other types of device connections, such as USB, IEEE 1394, orthe like.

Although FIG. 1 illustrates a single computing device 12 and attributesall control and processing functions to that single computing device 12,in other examples, system 10 may include multiple computing devices 12,e.g., a plurality of computing devices 12. In general, control andprocessing functions described herein may be divided among one or morecomputing devices. For instance, system 10 may include controller forenergy delivery device 16, powder delivery device 14, and stage 20, aseparate controller for PFMS 18, and a separate computing device foranalyzing data obtained by PFMS 18. As another example, system mayinclude a dedicated controller for each of energy delivery device 16,powder delivery device 14, stage 20, and PFMS 18, and a separatecomputing device for coordinating control of energy delivery device 16,powder delivery device 14, stage 20, and/or PFMS 18 and analyzing dataobtained by PFMS 18. Other examples of computing system architecturesfor controlling system 10 and analyzing data obtained from system 10will be apparent and are within the scope of this disclosure.

Computing device 12 may be configured to control operation of powderdelivery device 14, energy delivery device 16, optical system 18, and/orstage 20 to position component 22 relative to powder delivery device 14,energy delivery device 16, optical systeml8, and/or stage 20. Forexample, as described above, computing device 12 may control stage 20and powder delivery device 14, energy delivery device 16, and/or one ormore components of optical system 18 to translate and/or rotate along atleast one axis to position component 22 relative to powder deliverydevice 14, energy delivery device 16, and/or optical systeml8.Positioning component 22 relative to powder delivery device 14, energydelivery device 16, and/or optical system 18 may include positioning apredetermined surface (e.g., a surface to which material is to be added)of component 22 in a predetermined orientation relative to powderdelivery device 14, energy delivery device 16, and/or optical system 18.

Computing device 12 may be configured to control system 10 to depositlayers 24 and 26 to form component 22. As shown in FIG. 1 , component 22may include a first layer 24 and a second layer 26, although manycomponents may be formed of additional layers, such as tens of layers,hundreds of layers, thousands of layers, or the like. Component 22 inFIG. 1 is simplified in geometry and the number of layers compared tomany components formed using additive manufacturing techniques. Althoughtechniques are described herein with respect to component 22 includingfirst layer 24 and second layer 26, the technique may be extended tocomponents 22 with more complex geometry and any number of layers.

To form component 22, computing device 12 may control powder deliverydevice 14 and energy delivery device 16 to form, on a surface 28 offirst layer of material 24, a second layer of material 26 using anadditive manufacturing technique. Computing device 12 may control energydelivery device 16 to deliver energy 34 to a volume at or near surface28 to form melt pool 32. For example, computing device 12 may controlthe relative position of energy delivery device 16 and stage 20 todirect energy to the volume. Computing device 12 also may control powderdelivery device 14 to deliver powder stream 30 to melt pool 32. Forexample, computing device 12 may control the relative position of powderdelivery device 14 and stage 20 to direct powder stream 30 at or on tomelt pool 32. Computing device 12 may control powder delivery device 14and energy delivery device 16 to move energy 34 and powder stream 30along build surface 28 in a pattern until layer 26 is complete.Computing device 12 then may control a z-axis position of stage 20and/or powder delivery device 14 and energy delivery device 16 such thatmelt pool 32 will be formed on surface 36 of second layer 26, and maycontrol powder delivery device 14 and energy delivery device 16 to moveenergy 34 and powder stream 30 along build surface 28 in a pattern untillayer 26 is complete. Computing device 12 may control powder deliverydevice 14 and energy delivery device 16 similarly until all layers areformed to define a completed component 22.

In accordance with techniques of this disclosure, system 10 includes apowder flow monitoring system (PFMS) 18. PFMS 18 is configured to imageat least a portion of powder stream 30 to detect powder flowing betweenpowder delivery device 14 and build surface 28. For example, PFMS 18 mayinclude an illumination device and an imaging device. In some examples,the illumination device may include one or more light source. Forinstance, the illumination device may include one or more structuredlight devices, such as one or more lasers. The illumination device isconfigured to illuminate a plane of powder stream 30 at image plane 38,e.g., a plane substantially perpendicular to an axis extending betweenpowder delivery device 14 and build surface 28.

The imaging device of PFMS 18 is configured to image at least some ofthe illuminated powder. The imaging device may have a relatively highdata acquisition speed (e.g., frame rate), such greater than 1000 Hz.Because of the velocity of the powder in powder stream 30, even such aframe rate may image only a fraction of the powder flowing betweenpowder delivery device 14 and build surface 28.

In some examples, PFMS 18 also includes a housing configured to enclosethe illumination device and the imaging device. The housing may beconfigured to protect the illumination device and the imaging devicefrom damage due to the harsh conditions to which PFMS 18 may be exposedduring use. For example, the housing may protect the illumination deviceand the imaging device from powder deflections from powder stream 30 offbuild surface 28, may cool the illumination device and the imagingdevice to remove heat incident on PFMS 18 from melt pool 32 and energydelivery device 16, or the like.

PFMS 18 may be positionally fixed relative to powder delivery device 14and/or energy delivery device 16, e.g., in the x-y plane shown in FIG. 1. This may help maintain a relative x-y position of PFMS 18 and theimage plane of the imaging device relative to powder stream 30. This mayfacilitate analysis of image data captured by the imaging device.

PFMS 18 may be movable in the z-axis direction of FIG. 1 (e.g., parallelto a longitudinal axis extending from powder delivery device 14 to buildsurface 28). This may enable movement of image plane 38 along the z-axisof FIG. 1 (e.g., parallel to a longitudinal axis extending from powderdelivery device 14 to build surface 28). This may allow PFMS 18 to imagepowder stream 30 at different positions between powder delivery device14 and build surface 28. In this way, PFMS 18 may analyze powder stream30 along powder stream 30 to help determine parameters of powder stream30 along its length.

In some example, PFMS 18 may be positionally fixed relative to powderdelivery device 14 and/or energy delivery device 16 and movable parallelto a longitudinal axis extending from powder delivery device 14 to buildsurface 28 by an adjustable z-stage 40. Adjustable z-stage 40 may beattached to energy delivery device 16, powder delivery device 14, or aportion of system 10 that moves energy delivery device 16 and/or powderdelivery device 14, such that PFMS 18 moves in the x-y axis inregistration with energy delivery device 16 and/or powder deliverydevice 14.

Adjustable z-stage 40 may be controlled by computing device 12 toposition PFMS 18 and image plane 38 relative to powder stream 30.Further, computing device 12 may control adjustable z-stage 40 to movePFMS 18 vertically and out of the way to allow powder delivery device 16and energy delivery device 16 access to physically constrained areas,e.g., between vanes of a doublet or triplet of a nozzle guide vane for agas turbine engine.

FIG. 2 is a conceptual and schematic diagram illustrating an examplepowder flow monitoring system 50 configured to monitor powder flowbetween a powder delivery device 52 and a build surface (not shown inFIG. 2 ) during an additive manufacturing technique. Powder deliverydevice 52 may be an example of powder delivery device 14 of FIG. 1 , andPFMS may be an example of PFMS 18 of FIG. 1 .

Powder delivery device 52 includes a deposition head 54 that carries aplurality of powder nozzles 56. Plurality of powder nozzles 56 output apowder stream 58 toward the build surface. As shown in FIG. 2 , thepowder stream 58 may be focused at a focal plane, such that powderstream 58 is converging toward the focal plane and diverging away fromthe focal plane.

PFMS 18 includes a housing 60 (also referred to as an enclosure), whichencloses an imaging device 62 and an illumination device 64. In someexamples, imaging device 62 may be a high-speed camera and illuminationdevice 64 may be laser illuminator. Housing 60 is attached to anadjustable z-stage 66 by a bracket 68.

Housing 60 is configured to enclose imaging device 62 and illuminationdevice 64 and help protect imaging device 62 and illumination device 64from a surrounding environment. For instance, housing 60 may beconfigured to surround imaging device 62 and illumination device 64 andprevent any powder that reflects from the build surface toward PFMS 18from impacting imaging device 62 or illumination device 64.

Further, housing 60 may be configured to cool imaging device 62 andillumination device 64. Imaging device 62 and illumination device 64 maybe exposed to heat from the melt pool at the build surface and energyfrom the energy delivery device. Imaging device 62 and illuminationdevice 64 may be relatively sensitive to heat and have improvedoperational lifetime if maintained and operated below a certaintemperature. PFMS 50 may include a cooling system 70 configured toremove heat from within housing 60 to cooling imaging device 62 andillumination device 64. For instance, cooling system 70 may includecooling fluid circuit through which a cooling fluid flows, and housing60 may include part of the cooling circuit. In some examples, housing 60may be formed from a material having relatively high thermalconductivity, such as aluminum, to help transfer heat from withinhousing 60 to cooling system 70 (e.g., a cooling fluid flowing throughcooling system 70).

In some examples, housing 60 may be configured to position, orient, andallow light to pass through to or from imaging device 62 andillumination device 64, respectively. For example, housing 60 mayinclude one or more apertures or view ports through which light canpass. In some examples, the apertures or view ports may be filled with amaterial 72 that is substantially transparent to wavelengths ofinterest, e.g., wavelengths of illumination device 64. Additionally oralternatively, the apertures or view ports may be filled with a material72 that is not substantially transparent to at least some otherwavelengths, e.g., wavelengths associated with energy 34 (FIG. 1 ) oremitted by melt pool 32 (FIG. 1 ). In this way the material 72 thatfills the apertures or view ports may, in some examples, act as a filterto attenuate or remove wavelengths associated with energy 34 (FIG. 1 )and/or emitted by melt pool 32 (FIG. 1 ) while passing wavelengthsassociated with PFMS 50.

As described above, PFMS 50 may be configured to measure powder flow ofpowder stream 58 (FIG. 2 ) at one or more axial (or longitudinal)locations of powder stream 58 and determine one or more parametersassociated with the powder flow. For instance, illumination device 64may illuminate powder of powder stream 58 in a plane orientedsubstantially orthogonal to a longitudinal axis that extends from powderdelivery device 52 to the build surface. PFMS 50 may be positioned at aselected axial or longitudinal location to image a selected axial orlongitudinal position between powder delivery device 52 and the buildsurface. Imaging device 62 may be configured to image at least some ofthe illuminated powder. FIG. 3 is a conceptual diagram illustrating anexample of portions of a powder stream imaged by a powder flowmonitoring system.

As shown in FIG. 3 , since powder is flowing in powder stream 58 at arelatively high velocity, imaging device 62 may not capture images ofall the powder in powder stream 58. The fraction of powder that imagingdevice 62 captures images of may be a function of average powdervelocity at the image plane and a frame rate or capture speed of imagingdevice 62. This is represented in FIG. 3 as “sampled” particles and“missed population” particles. The fraction of particles imaged byimaging device 62 may, in some examples, be less than about 50%, lessthan about 40%, less than about 30%, less than about 25%, less thanabout 20%, or less than about 15%.

PFMS 50 may include a computing device (e.g., computing device 12 ofFIG. 1 ) configured to analyze images captured by imaging device 62 toidentify a number of particle detections in each captured image and,optionally, derive further parameters from the number of particledetections. As such, computing device 12 may be configured to receiveimage data representing an image captured by imaging device 62. Theimage data may include representations of illuminated powder of powderstream 58, as imaged by imaging device 62 (e.g., as captured in an imageframe by imaging device 62). Computing device 12 may be configured togenerate a representation of powder stream based on the image data andoutput the representation of the powder stream for display at a displaydevice.

For instance, computing device 12 may be configured determine a powdermass flow represented by the image data. To do so, computing device 12may be configured to identify a number of powder particles within eachimage frame. In some examples, computing device 12 additionally may beconfigured to identify a size and/or shape of each powder particlewithin each image frame. Computing device 12 may be configured toimplement any suitable image analysis technique to identify powderparticles, and, optionally, size and/or shape of powder particles.

Once computing device 12 has identified a number of powder particleswithin an image frame, computing device 12 may be configured todetermine a mass flow based on the number of powder particles. Forexample, computing device 12 may be configured to determine the massflow based on a calibration equation or calibration curve. FIG. 4 is anexample calibration curve of particle detections versus mass flow. Asshown in FIG. 4 , the relationship between particle detections may besubstantially linear.

The relationship between particle detections and mass flow may bedetermined experimentally. For instance, the relationship betweenparticle detections and mass flow may be determined for each powder type(e.g., composition, size distribution, or both), as each powder type mayhave a different relationship between particle detections and mass flow.The relationship may be determined experimentally by flowing a knownmass of powder at a known rate, and imaging the powder. By doing thismultiple times at multiple rates, the calibration curve may begenerated. The curve, in the form of an equation, a look-up table, orthe like, may be stored in computing device 12, and computing device 12may use the calibration curve to determine mass flow of a similar typeof powder at a different flow rate based on particle detections.

In some examples, computing device 12 may receive image datarepresentative of a sequence of images of illuminated powder in powderstream 58. Each image may be associated with a time. As such, computingdevice 12 may select one or more images of the sequence of images andanalyze the one or more images. For each selected image, computingdevice 12 may be configured to identify a number of particle detectionsand, optionally, determine a mass flow associated with powder stream 58for each image frame.

Computing device 12 may be configured to generate a representation ofthe powder stream based on the image data. The representation may be anumber, such as a number of detections, a detection rate, a mass flow, amass flow rate, or the like. Alternatively, or additionally, therepresentation may be a user interface screen that graphicallyrepresents the powder stream.

FIG. 5 is an example graphical user interface screen 80 illustratingheat maps 82, 84, 86, and 88 of mass flow for each of four regions ofinterest. In the example shown in FIG. 5 , a first heat map 82represents a mass flow rate (measured in mg/min) for a first region ofinterest, which includes an upper left portion of a powder stream (e.g.,nearer to the powder delivery device than the build surface andassociated with a left nozzle of a plurality of nozzles). Second heatmap 84 represents a mass flow rate (measured in mg/min) for a secondregion of interest, which includes an upper right portion of a powderstream (e.g., nearer to the powder delivery device 52 than the buildsurface and associated with a right nozzle of a plurality of nozzles).To collect image data from which computing device 12 may determine thirdheat map 86 and fourth heat map 88, PFMS 50 may be positioned at afirst, upper position along the longitudinal axis that extends betweenpowder delivery device 52 and the build surface. Computing device 12 maythen select a first subset of the image data from an image frame asrepresentative of the left portion of the powder stream, e.g., based onidentifying a cluster of powder detections, and may select a secondsubset of the image data from an image frame as representative of theright portion of the powder stream, e.g., based on identifying a clusterof powder detections.

Graphical user interface screen 80 also includes a third heat map 86 anda fourth heat map 88. Third heat map 86 represents a mass flow rate(measured in mg/min) for a third region of interest, which includes alower left portion of a powder stream (e.g., nearer to the build surfacethan the powder delivery device 52 and associated with a left nozzle ofa plurality of nozzles). Fourth heat map 88 represents a mass flow rate(measured in mg/min) for a fourth region of interest, which includes alower right portion of a powder stream (e.g., nearer to the buildsurface that powder delivery device 52 and associated with a rightnozzle of a plurality of nozzles). To collect image data from whichcomputing device 12 may determine first heat map 82 and second heat map84, PFMS 50 may be positioned at a second, lower position along thelongitudinal axis that extends between powder delivery device 52 and thebuild surface. Computing device 12 may then select a first subset of theimage data from an image frame as representative of the left portion ofthe powder stream, e.g., based on identifying a cluster of powderdetections, and may select a second subset of the image data from animage frame as representative of the right portion of the powder stream,e.g., based on identifying a cluster of powder detections.

Although graphical user interface screen 80 includes four regions ofinterest and corresponding mass flow rates, computing device 12 analyzeany selected number of regions of interest, e.g., one region ofinterest, two regions of interest, three regions of interest, or moreregions of interest. In general computing device 12 or a user ofcomputing device 12 may cause computing device 12 to separate powderstream 58 into any number of regions of interest, and analyze image dataassociated with the regions of interest. Further, although FIG. 5illustrates mass flow rate, in other examples, graphical user interfacescreen 80 may include a detection rate, in addition to or instead of themass flow rate.

In some examples, computing device 12 may determine each heat map ofheat maps 82, 84, 86, and 88 based on a single image frame (e.g., afirst common image frame for heat maps 82 and 84 and a second commonimage frame for heat maps 86 and 88, or a single, different image framefor each of heat maps 82, 84, 86, and 88). Computing device 12 may useinformation regarding the number of powder detections, the relationshipbetween powder detections and mass flow, and a known velocity of thepowder to determine the mass flow rate. In other examples, computingdevice 12 may aggregate or integrate powder detections or mass from aplurality of image frames to generate heat maps 82, 84, 86, and 88.

FIG. 6 is another example graphical user interface screen 90illustrating a second type of graphical representation of instantaneousmass flow versus time for each of six regions of interest. In FIG. 6 ,the regions of interest may include a top region, a bottom region, anupper left region, an upper right region, a lower left region, and alower right region. The top region is a sum of the upper left and upperright regions, and the bottom region is a sum of the lower left andlower right regions. Like the example shown in FIG. 5 , to collect theimage data for the top regions, upper left region, and upper rightregion, PFMS 50 may be positioned to image a first image plane, nearerto powder delivery device 52 than the build surface. To collect theimage data for the bottom region, upper left region, and upper rightregion, PFMS 50 may be positioned to image a second image plane, nearerto the build surface than to powder delivery device 52.

To compute an instantaneous mass flow, computing device 12 may beconfigured to analyze a single image frame to produce each instantaneousmass flow, rather than combining multiple image frames to produce aninstantaneous mass flow. For instance, computing device 12 may receive afirst image frame associated with the first, upper image plane andanalyze the first image frame to determine a data point for the top massflow plot, the upper left mass flow plot, and the upper right mass flowplot. Computing device 12 then may receive a second image frame,captured at a later time than the first image frame, and analyze thesecond image frame to determine a data point for the top mass flow plot,the upper left mass flow plot, and the upper right mass flow plot.Computing device 12 may repeat this analysis of individual image framesto produce data points over time for the top mass flow plot, the upperleft mass flow plot, and the upper right mass flow plot. Computingdevice 12 may perform a similar analysis of image frames associated withthe second, lower image plane to determine data points for the bottommass flow plot, the lower left mass flow plot, and the lower right massflow plot.

The plots of mass flow versus time shown in FIG. 6 may help an operatoror computing device 12 determine a flow consistency for each region ofinterest. This may help the user or computing device 12 identify flowpulsing, which may be indicative of wear or damage to a portion of thesystem, such as a powder nozzle, channel within powder delivery device52, a valve, or the like.

In some examples, computing device 12 may be configured to generate andoutput a representation of a geometrical distribution of powder withinpowder stream 58. For example, FIG. 7A is an example plot of particledetections as a function of radius and angle for a region of interest.FIG. 7B is an example plot of particle detections as a function ofradius along a radius of FIG. 7A. Computing device 12 may be configuredto receive image data representing illuminated powder of powder stream58 between powder delivery device 50 and a build surface of a component,with PFMS 50 positioned at a selected location along the longitudinalaxis extending between powder delivery device 50 and the build surface.Computing device 12 then may analyze the image data (including a singleimage frame or a sequence of image frames) to determine a geometricdistribution of powder within powder stream 58.

For instance, computing device 12 may be configured to determinecorresponding locations of particle detections according to a selectedcoordinate system. For instance, computing device 12 may be configuredto determine corresponding locations of particle detections according toa polar coordinate system, a cartesian coordinate system, or the like.

Computing device 12 may be configured to determine a powder distributionfor a region of interest based on the corresponding locations ofparticle detections. For instance, computing device 12 may be configuredto select a radius (in a polar coordinate system) and determine a powderdistribution along the radius. As another example, computing device 12may be configured to select a sector of the polar coordinate system(e.g., a quadrant or a smaller or larger sector) and determine a radialpowder distribution within the sector.

FIG. 7A illustrates an example of a portion of a powder distributionwithin a polar coordinate system. As shown in FIG. 7A, in some examples,at some axial locations of a powder stream, the powder stream may beannular. For instance, the powder stream may be conical above the focalplane, with an annular distribution of powder in the plane orthogonal toan axis of the cone. As such, powder distribution may be concentratedaround a radial distance in a powder distribution curve. In someexamples, the powder distribution curve may be substantially similar toa bell curve or gaussian curve. FIG. 7B illustrates an example plot of apowder distribution curve along the radius shown in FIG. 7A. As shown inFIG. 7B, the powder distribution curve may be characterized by a meanintensity (which may be proportional to a number of particledistributions as a function of radius), and a radius at the meanintensity. Additionally, although not shown in FIG. 7B, computing device12 also may determine other statistical properties of the powderdistribution, such as a standard deviation of the powder distributioncurve, or the like.

In other examples, such as at different axial positions of powder stream58, the powder distribution may be different, e.g., may not be annular.For instance, at or near the focal plane of powder stream 58, the powderdistribution may be approximately circular with a gaussian distributionof powder. As another example, where powder delivery device 52 includesmultiple discrete powder nozzles 56, the powder distribution atlocations near the powder delivery device 52 may be concentrated inmultiple flows corresponding to the number and position of the discretepowder nozzles 56.

In some examples, rather than determining the powder distribution curvealong a single radius, computing device 12 may determine powderdistribution curve for a sector of a the polar coordinate system. Forinstance, FIG. 8A is an example plot of powder distribution in an imageplane plotted in polar coordinates. As shown in FIG. 8A, the image planeand polar coordinate system has been divided into four substantiallyequal segments, e.g., into quadrants. Each quadrant subtends an angle ofabout 90 degrees. FIG. 8B is an example plot of number of powderdetections versus radial distance for each of the four quadrants shownin FIG. 8A. Computing device 12 may be configured to generate the plotshown in FIG. 8B by associated each powder detection with a coordinate(e.g., radius and angle) and binning particle detections into binsassociated with a subtended angle (e.g., quadrant) and range of radiusvalues.

In some examples, computing device 12 may generate a representation ofthe powder stream from image data associated with different positions ofPFMS 50 along the axis of powder stream 58. This may enable athree-dimensional representation of powder stream 58 and powderdistribution (and mass flow) within powder stream 58 atthree-dimensional locations of powder stream 58. For instance, computingdevice 12 may control PFMS 50 to be positioned at a selected axialposition of powder stream 58 and to collect at least one image (e.g., animage or a sequence of images) at the selected axial position. Computingdevice 12 may control PFMS 50 to be positioned at a second selectedaxial position of powder stream 58 and to collect at least one image(e.g., an image or a sequence of images) at the second selected axialposition. Computing device 12 may repeat this for any selected number ofaxial positions.

Computing device 12 then may analyze the at least one image frame ateach axial position to determine coordinates for powder detections ateach axial position, e.g., in a polar coordinate or cartesian coordinatesystem. For example, FIG. 9A is an example plot of powder detections inan image plane (at a selected axial position of powder stream 58)plotted in cartesian coordinates.

Computing device 12 also may associate each axial position with an axialcoordinate, e.g., within a cylindrical or cartesian coordinate system.This may allow computing device 12 to assemble powder detections fromdifferent axial locations to generate a three-dimensional representationof powder stream 58 within a cylindrical or cartesian coordinate system.For example, FIG. 9B is an example three-dimensional plot of powderdetections plotted in cartesian coordinates.

FIG. 10A is an example plot of particle detections in an image planeplotted in cartesian coordinates. FIG. 10B is an examplethree-dimensional plot of particle detections plotted in cartesiancoordinates. As shown in the comparison of FIGS. 9A and 10A, powderstream 58 may have a different shape in the image plane at differentaxial locations of powder stream 58. For example, at some axiallocations, as shown in FIG. 9A, powder stream 58 may have asubstantially annular shape. As another example, at other axiallocations, as shown in FIG. 10A, powder stream 58 may have asubstantially elliptical or substantially circular shape.

In addition to generally representing a shape of powder stream 58, thetechniques of plotting powder detections within a coordinate system alsomay facilitate analysis of changes to system parameters. For example,FIGS. 9A and 10A each show differences in powder distribution due tochanges in carrier gas flow rate (a flow rate of gas entraining thepowder and delivering the powder to powder delivery device 52 and out ofnozzles 56). As shown in FIGS. 9A and 10A, changing carrier gas flowrates may affect a quality of focus of powder stream 58. FIGS. 9B and10B illustrate the three-dimensional shape of powder stream 58 for thetwo different carrier gas flow rates, and similarly show changes in theshape of powder stream 58 due to the differences in carrier gas flowrates.

Although FIGS. 9A-10B show how representing a shape of powder stream 58based on particle detections can be used to evaluate changes in carriergas flow rates, representing a shape of powder stream 58 based onparticle detections can also be used to analyze effects of otherparameters, e.g., stand-off height; powder feed rate; nozzle size,shape, or number; valve position; and/or wear or damage to one or morecomponents of the system (e.g., nozzles 56, or channels or valves withinpowder delivery device 52). In this way, the techniques described hereinmay enable an operator or designer to better understand operation of thesystem and effects of operating parameters on powder stream 58.

In some examples, representing a shape of powder stream 58 based onparticle detections may be used to detect a clog within the system ordamage to a component of the system. For example, FIG. 11 is an exampleplot of powder detections in an image plane plotted in polarcoordinates. The polar coordinates are divided into four quadrants, eachquadrant corresponding to a 90 degree sector. Quadrant 1 extends from 0to 90 degrees, quadrant 2 extends from 90 to 180 degrees, quadrant 3extends from 180 degrees to 270 degrees, and quadrant 4 extends from 270degrees to 0 degrees. As shown in FIG. 11 , the powder distribution isasymmetric. Near the boundary of quadrants 2 and 3 (between about 145degrees and 190 degrees), the powder distribution is low, while near theboundary of quadrants 4 and 1 (about 330 to 30 degrees), the powderdistribution is high. This may indicate a clog within a nozzle directingpowder to between 145 degrees and 190 degrees or may indicate damage toa nozzle directing powder to between about 330 to 30 degrees, or both,such that the resulting powder flow is asymmetric.

FIG. 12 is an example plot of particle detections in an image planeplotted in polar coordinates. The data shown in FIG. 12 is from the samepowder stream 58 as shown in FIG. 11 , but at a different axial positionalong powder stream 58. FIG. 12 similarly shows a low powderdistribution in quadrants 2 and 3 and a high powder distribution inquadrants 1 and 4. Together, FIGS. 11 and 12 may indicate a clog withina nozzle directing powder to between 145 degrees and 190 degrees, or mayindicate damage to a nozzle directing powder to between about 330 to 30degrees, or both, such that the resulting powder flow is asymmetric.

As described above with respect to FIGS. 7A-8B, computing device 12 maybe configured to analyze a powder distribution along a radius or withina sector and determine one or more metrics characterizing the powderdistribution. In some examples, computing device 12 may determine one ormore metrics characterizing the powder distribution as a function oftime. FIG. 13 is an example plot of powder range and standard deviationversus time for each of four image sectors (e.g., quadrants). Computingdevice 12 may select a region of interest (e.g., a quadrant) within theimage plane; for each of a plurality of image frames in a sequence ofimage frames, determine a radial distance within the region of interestat which a mean intensity of the powder locations occurs and determine astandard deviation of the radial distance; and generate a plotillustrating the radial distance and the standard deviation of theradial distance for the region of interest versus time. The results ofthis analysis are shown in FIG. 13 . As shown in FIG. 13 , the powderrange and standard deviation may change in response to powderagglomeration (e.g., a clog). Similarly, powder range and standarddeviation may change in response to nozzle wear or damage. For instance,a clog, agglomeration, or nozzle wear or damage may cause an increase inpowder range and standard deviation (as suggested by FIGS. 11 and 12 ).This may enable computing device 12 or an operator of computing device12 to detect a clog, agglomeration, or nozzle wear or damage rapidlyafter the clog, agglomeration, or nozzle wear or damage occurs.

FIGS. 14A-14C illustrate an example of how computing device 12 maydetect a damaged nozzle using powder distribution (e.g., a heat map likethat shown in FIG. 5 ). FIGS. 14A and 14B are example heat mapsillustrating powder mass flow at different z-axis heights (axiallocations) of a powder stream 58. As shown in both FIGS. 14A and 14B, arelatively high powder distribution is concentrated in a lower rightquadrant of powder stream 58. FIG. 14C is an image of the powder nozzleused to form the powder flow represented in FIGS. 14A and 14B, showingdamage in the powder nozzle in the lower right quadrant. As such, thissuggests that heat maps of powder distribution may be used (e.g., bycomputing device 12) to identify a damaged nozzle.

In some examples, data regarding powder stream 58 collected using PFMS50 may be used to control operation of an additive manufacturing system.FIG. 15 is flow diagram illustrating an example technique forcontrolling an additive manufacturing system based on data regardingpowder stream 58 collected using PFMS 50. The flow diagram of FIG. 15will be described with concurrent reference to system 10 of FIG. 1 andPFMS 50 and powder delivery device 52 of FIG. 2 . However, system 10 andPFMS 50 and powder delivery device 52 may be used to perform othertechniques, and other systems and devices may be used to perform thetechnique of FIG. 15 .

The technique of FIG. 15 includes receiving, by one or more computingdevices 12, image data representing illuminated powder of a powderstream 58 between a powder delivery device 52 of an additivemanufacturing system and a build surface of a component (82). Asdescribed above, e.g., with reference to FIG. 2 , computing device 12may be configured to receive image data representing an image capturedby imaging device 62. The image data may include representations ofilluminated powder of powder stream 58, as imaged by imaging device 62(e.g., as captured in an image frame by imaging device 62). In someexamples, computing device 12 may receive image data representative of asequence of images of illuminated powder in powder stream 58. Each imagemay be associated with a time.

The technique of FIG. 15 also includes determining, by one or morecomputing devices 12, at least one metric associated with the powderstream based on the received image data (84). In some examples, the atleast one metric includes a mass flow rate or a powder distributionwithin powder stream 58. The at least one metric may be associated witha single image frame or a series of image frames and may be associatedwith an entire image frame or a region of interest within an imageframe. For instance, as shown in FIG. 5 , the at least one metric mayinclude a plurality of metrics: powder detections from one or more imageframes within a plurality of regions of interest. As another example,the at least one metric may include one or more corresponding powderdistribution parameter within a sector (e.g., quadrant) of a polarcoordinate system, as shown in FIGS. 7A-8B, 11, and 12 .

The at least one metric may be indicative of one or more property ofpowder stream 58, including, for example, powder mass flux for powderstream 58, powder mass flux for a region of interest of powder stream58, wear or damage to one or more powder nozzles 56, powder distributionwithin powder stream 58, clogging of one or more powder nozzles 56, flowof the carrier gas in which powder is entrained, flow of a purge gas, orthe like.

The technique of FIG. 15 further includes determining, by one or morecomputing devices 12, whether the at least one metric indicates anabnormal state of the at least one metric (86). For instance, one ormore computing devices 12 may be configured to compare the at least onemetric associated with each region of interest (of a plurality ofregions of interest) to the at least one metric associated with eachother region of interest. For example, one or more computing devices 12may be configured to compare a corresponding powder distributionparameter associated with each quadrant to each other correspondingpowder distribution parameter. As another example, one or more computingdevices 12 may be configured to compare a corresponding powder mass fluxassociated with each quadrant to each other corresponding powder massflux.

One or more computing devices 12 may be configured to determine that theat least one metric indicates the abnormal state in response to thecomparison showing differences between the metrics above a thresholddifference value. For instance, with reference to FIG. 12 , one or morecomputing devices 12 may compare a powder mass flux associated withquadrant 1 to powder mass fluxes associated with quadrants 2, 3, and 4,may compare a powder mass flux associated with quadrant 2 to powder massfluxes associated with quadrants 3 and 4, and may compare a powder massflux associated with quadrant 3 to powder mass fluxes associated withquadrant 4, such that each powder mass flux is compared to each otherpowder mass flux. In the example of FIG. 11 , the powder mass fluxes forquadrants 1 and 4 differ from the powder mass fluxes for quadrants 2 and3, and may differ by more than a threshold difference value. This mayindicate an abnormal state. As a counter example, the mass fluxes foreach of the quadrants shown in FIG. 8A are substantially similar and maynot differ by more than a threshold difference value. This may indicatea normal state.

One or more computing devices 12 alternatively or additionally may beconfigured to determine whether the at least one metric indicates anabnormal state of the at least one metric (86) by at least comparing theat least one metric to a baseline range of values. For instance, one ormore computing devices 12 may be configured to compare a powder massflux for a plane of powder stream 58 to a set powder mass flux. Asanother example, one or more computing devices 12 may be configured tocompare a powder mass flux for a region of interest (e.g., a sector orquadrant of a plane of powder stream 58) a set or expected powder massflux for the region of interest. One or more computing devices 12 may beconfigured to determine that the at least one metric indicates theabnormal state in response to the at least one metric being outside ofthe baseline range of values (e.g., differs for the set value orexpected value or differs for the set value or expected value by greaterthan a threshold amount).

The technique of FIG. 15 additionally includes causing, by one or morecomputing devices 12, the additive manufacturing system to perform atleast one action in response to the at least one metric indicating theabnormal state (88). In some examples, one or more computing devices 12may be configured to control at least one operating parameter of theadditive manufacturing system in response to the at least one metricindicating the abnormal state (88). The at least one operating parametermay include a powder feed rate, a carrier gas flow rate, a position ofpowder delivery device 52, a purge gas flow rate, or combinationsthereof. The at least one operating parameter may be an overall flowrate through powder delivery device 52, or a flow rate to a selected(e.g., individual) nozzle 56 of powder delivery device 52.

The at least one action may depend on the abnormal state indicated bythe at least one metric. For instance, if the at least one metricindicates a powder mass flux that is lower than a set powder mass flux,one or more computing devices 12 may be configured to cause a powderfeed rate to nozzles 56 to increase, e.g., by increasing a carrier gasflow rate through a powder source, increasing a powder agitation ratewithin the powder source to entrain more powder in the carrier gas, orthe like. Alternatively, if the at least one metric indicates a powdermass flux that is lower than a set powder mass flux for a single nozzle,one or more computing devices 12 may be configured to cause a powderfeed rate to the single nozzle to increase, e.g., by controlling a valveassociated with the single nozzle to open further and permit greaterpowder flow to the single nozzle.

In some implementations, one or more computing devices 12 may beconfigured to place powder delivery device 52 in a recovery state whilecontrolling the at least one operating parameter of the additivemanufacturing system (88). One or more computing devices 12 may causepowder delivery device 52 to place powder delivery device 52 in therecovery state by at least moving powder delivery device 52 to aposition away from the deposition location, such that powder deliverydevice 52 is no longer directing powder and energy to the build surface.At this position, one or more computing devices 12 may control the atleast one operating parameter. By positioning powder delivery device 52at a position away from the deposition location, one or more computingdevices 12 may control the at least one operating parameter withoutaffecting deposition of the powder in the melt pool. This may be useful,as changes in operating parameters may propagate through the additivemanufacturing system at a relatively low rate. One or more computingdevices 12 may cause powder delivery device 52 remain in the recoverystate until the at least one operating parameter has stabilized to asubstantially constant value.

In some examples, one or more computing devices 12 may iterativelycontrol the at least one operating parameter, e.g., while powderdelivery device 52 is in the recovery state. For example, one or morecomputing devices 12 may change the at least one operating parameter toa new value, wait for the at least one operating parameter hasstabilized to a substantially constant value, and determine and analyzethe at least one metric to determine whether the at least one metricindicates a normal or abnormal state. In response to determining thatthe at least one metric again indicates the abnormal state, one or morecomputing devices 12 may change the at least one operating parameter toa new value, wait for the at least one operating parameter hasstabilized to a substantially constant value, and determine and analyzethe at least one metric to determine whether the at least one metricindicates a normal or abnormal state. One or more computing devices 12may continue to iterate until determining that the at least one metricindicates a normal state.

In some examples, one or more computing devices 12 may be configuredcontrol the at least one operating parameter of the additivemanufacturing system (88) to clean one or more nozzles 56. For instance,one or more computing devices 12 determine that one or more of nozzles56 is clogged, e.g., as described above with respect to FIGS. 12-14 . Inresponse, one or more computing devices 12 may be configured to causepowder delivery device 52 to move against a scrubbing surface to scrub aclog from one or more of nozzles 56. Alternatively, or additionally, oneor more computing devices 12 may be configured to cause a relativelyhigh flow rate of gas (e.g., purge gas or carrier gas) through thenozzle identified to be clogged to attempt to force the clog from thenozzle identified to be clogged.

In this way, a PFMS may be used to obtain data based upon which one ormore computing devices 12 may control operation of the additivemanufacturing system. This may enable more accurate control of theadditive manufacturing system and the resulting additively manufacturedcomponent.

The techniques described in this disclosure may be implemented, at leastin part, in hardware, software, firmware, or any combination thereof.For example, various aspects of the described techniques may beimplemented within one or more processors, including one or moremicroprocessors, digital signal processors (DSPs), application specificintegrated circuits (ASICs), field programmable gate arrays (FPGAs), orany other equivalent integrated or discrete logic circuitry, as well asany combinations of such components. The term “processor” or “processingcircuitry” may generally refer to any of the foregoing logic circuitry,alone or in combination with other logic circuitry, or any otherequivalent circuitry. A control unit including hardware may also performone or more of the techniques of this disclosure.

Such hardware, software, and firmware may be implemented within the samedevice or within separate devices to support the various techniquesdescribed in this disclosure. In addition, any of the described units,modules or components may be implemented together or separately asdiscrete but interoperable logic devices. Depiction of differentfeatures as modules or units is intended to highlight differentfunctional aspects and does not necessarily imply that such modules orunits must be realized by separate hardware, firmware, or softwarecomponents. Rather, functionality associated with one or more modules orunits may be performed by separate hardware, firmware, or softwarecomponents, or integrated within common or separate hardware, firmware,or software components.

The techniques described in this disclosure may also be embodied orencoded in an article of manufacture including a computer-readablestorage medium encoded with instructions. Instructions embedded orencoded in an article of manufacture including a computer-readablestorage medium encoded, may cause one or more programmable processors,or other processors, to implement one or more of the techniquesdescribed herein, such as when instructions included or encoded in thecomputer-readable storage medium are executed by the one or moreprocessors. Computer readable storage media may include random accessmemory (RAM), read only memory (ROM), programmable read only memory(PROM), erasable programmable read only memory (EPROM), electronicallyerasable programmable read only memory (EEPROM), flash memory, a harddisk, a compact disc ROM (CD-ROM), a floppy disk, a cassette, magneticmedia, optical media, or other computer readable media. In someexamples, an article of manufacture may include one or morecomputer-readable storage media.

In some examples, a computer-readable storage medium may include anon-transitory medium. The term “non-transitory” may indicate that thestorage medium is not embodied in a carrier wave or a propagated signal.In certain examples, a non-transitory storage medium may store data thatcan, over time, change (e.g., in RAM or cache).

Various examples have been described. These and other examples arewithin the scope of the following clauses and claims.

Clause 1. A system comprising: one or more computing devices configuredto: receive image data representing illuminated powder of a powderstream between a powder delivery device of an additive manufacturingsystem and a build surface of a component; determine at least one metricassociated with the powder stream based on the received image data;determine whether the at least one metric indicates an abnormal state ofthe at least one metric; and cause the additive manufacturing system toperform at least one action in response to the at least one metricindicating the abnormal state.

Clause 2. The system of clause 1, wherein the one or more computingdevices is configured to determine the at least one metric by at least:determining a mass flow rate or powder distribution within the powderstream.

Clause 3. The system of clause 2, wherein the one or more computingdevices is configured to determine the at least one metric by at least:determining a mass flow rate or powder distribution for each region ofinterest of at least one region of interest of the powder stream.

Clause 4. The system of clause 2, wherein the one or more computingdevices is configured to determine the at least one metric by at least:determining a radial powder distribution for each region of interest ofat least one region of interest of the powder stream.

Clause 5. The system of clause 3 or 4, wherein the one or more computingdevices is configured to determine whether the at least one metricindicates an abnormal state by at least: comparing the at least onemetric associated with each region of interest to the at least onemetric associated with each other region of interest and determiningthat the at least one metric indicates the abnormal state in response tothe comparison showing differences between the metrics above a thresholddifference value.

Clause 6. The system of clause 1 or 2, wherein the one or more computingdevices is configured to determine whether the at least one metricindicates the abnormal state of the at least one metric by at least:comparing the at least one metric to a baseline range of values anddetermining that the at least one metric indicates the abnormal state inresponse to the at least one metric being outside of the baseline rangeof values.

Clause 7. The system of any one of clauses 1 to 6, wherein the one ormore computing devices is configured to cause the additive manufacturingsystem to perform at least one action by at least: controlling at leastone operating parameter of the additive manufacturing system.

Clause 8. The system of clause 7, wherein the at least one parametercomprises at least one of a powder feed rate or a carrier gas flow rate.

Clause 9. The system of clause 8, wherein the at least one parametercomprises at least one of a powder feed rate to a selected nozzle of thepowder delivery device or a carrier gas flow rate to a selected nozzleof the powder delivery device.

Clause 10. The system of clause 7, wherein the at least one parametercomprises a position of the powder delivery device.

Clause 11. The system of clause 10, wherein the one or more computingdevices is configured to cause the powder delivery device to moveagainst a scrubbing surface.

Clause 12. The system of clause 7, wherein the at last one parametercomprises a purge gas flow rate, and wherein the one or more computingdevices is configured to cause a relatively high purge gas flow ratethrough the deposition delivery device.

Clause 13. The system of any one of clauses 7 to 12, wherein the one ormore computing devices is configured to cause the additive manufacturingsystem to perform the at least one action by at least placing the powderdelivery device in a recovery state while controlling the at least oneoperating parameter of the additive manufacturing system.

Clause 14. A method comprising: receiving, by one or more computingdevices, image data representing illuminated powder of a powder streambetween a powder delivery device of an additive manufacturing system anda build surface of a component; determining, by the one or morecomputing devices, at least one metric associated with the powder streambased on the received image data; determining, by the one or morecomputing devices, whether the at least one metric indicates an abnormalstate of the at least one metric; and causing, by the one or morecomputing devices, the additive manufacturing system to perform at leastone action in response to determining that the at least one metricindicates the abnormal state.

Clause 15. The method of clause 14, wherein determining the at least onemetric comprises determining, by the one or more computing devices, amass flow rate or powder distribution within the powder stream.

Clause 16. The method of clause 15, wherein determining the at least onemetric comprises determining, by the one or more computing devices, amass flow rate or powder distribution for each region of interest of atleast one region of interest of the powder stream.

Clause 17. The method of clause 15, wherein determining the at least onemetric comprises determining, by the one or more computing devices, aradial powder distribution for each region of interest of at least oneregion of interest of the powder stream.

Clause 18. The method of clause 16 or 17, wherein determining whetherthe at least one metric indicates an abnormal state comprises comparing,by the one or more computing devices, the at least one metric associatedwith each region of interest to the at least one metric associated witheach other region of interest and determining that the at least onemetric indicates the abnormal state in response to the comparisonshowing differences between the metrics above a threshold differencevalue.

Clause 19. The method of clauses 14 or 15, wherein determining whetherthe at least one metric indicates the abnormal state of the at least onemetric comprises comparing, by the one or more computing devices, the atleast one metric to a baseline range of values and determining that theat least one metric indicates the abnormal state in response to the atleast one metric being outside of the baseline range of values.

Clause 20. The method of any one of clauses 14 to 18, wherein causingthe additive manufacturing system to perform at least one actioncomprises controlling, by the one or more computing devices, at leastone operating parameter of the additive manufacturing system.

Clause 21. The method of clause 20, wherein the at least one parametercomprises at least one of a powder feed rate or a carrier gas flow rate.

Clause 22. The method of clause 21, wherein the at least one parametercomprises at least one of a powder feed rate to a selected nozzle of thepowder delivery device or a carrier gas flow rate to a selected nozzleof the powder delivery device.

Clause 23. The method of clause 20, wherein the at least one parametercomprises a position of the powder delivery device.

Clause 24. The method of clause 13, wherein causing the additivemanufacturing system to perform at least one action comprises causingthe powder delivery device to move against a scrubbing surface.

Clause 25. The method of clause 20, wherein the at last one parametercomprises a purge gas flow rate, and wherein the causing the additivemanufacturing system to perform at least one action comprises causing,by the one or more computing devices, a relatively high purge gas flowrate through the deposition delivery device.

Clause 26. The method of any one of clauses 20 to 25, wherein causingthe additive manufacturing system to perform the at least one actioncomprises placing, by the one or more computing device, the powderdelivery device in a recovery state while controlling the at least oneoperating parameter of the additive manufacturing system.

What is claimed is:
 1. A system comprising: one or more computingdevices configured to: receive image data representing illuminatedpowder of a powder stream between a powder delivery device of anadditive manufacturing system and a build surface of a component;determine at least one metric associated with the powder stream based onthe received image data; determine whether the at least one metricindicates an abnormal state of the at least one metric; and cause theadditive manufacturing system to perform at least one action in responseto the at least one metric indicating the abnormal state.
 2. The systemof claim 1, wherein the one or more computing devices is configured todetermine the at least one metric by at least: determining a mass flowrate or powder distribution within the powder stream.
 3. The system ofclaim 2, wherein the one or more computing devices is configured todetermine the at least one metric by at least: determining a mass flowrate or powder distribution for each region of interest of at least oneregion of interest of the powder stream.
 4. The system of claim 2,wherein the one or more computing devices is configured to determine theat least one metric by at least: determining a radial powderdistribution for each region of interest of at least one region ofinterest of the powder stream.
 5. The system of claim 3, wherein the oneor more computing devices is configured to determine whether the atleast one metric indicates an abnormal state by at least: comparing theat least one metric associated with each region of interest to the atleast one metric associated with each other region of interest anddetermining that the at least one metric indicates the abnormal state inresponse to the comparison showing differences between the metrics abovea threshold difference value.
 6. The system of claim 1, wherein the oneor more computing devices is configured to determine whether the atleast one metric indicates the abnormal state of the at least one metricby at least: comparing the at least one metric to a baseline range ofvalues and determining that the at least one metric indicates theabnormal state in response to the at least one metric being outside ofthe baseline range of values.
 7. The system of claim 1, wherein the oneor more computing devices is configured to cause the additivemanufacturing system to perform at least one action by at least:controlling at least one operating parameter of the additivemanufacturing system.
 8. The system of claim 7, wherein the at least oneparameter comprises at least one of a powder feed rate or a carrier gasflow rate.
 9. The system of claim 8, wherein the at least one parametercomprises at least one of a powder feed rate to a selected nozzle of thepowder delivery device or a carrier gas flow rate to a selected nozzleof the powder delivery device.
 10. The system of claim 7, wherein the atleast one parameter comprises a position of the powder delivery device.11. The system of claim 10, wherein the one or more computing devices isconfigured to cause the powder delivery device to move against ascrubbing surface.
 12. The system of claim 7, wherein the at last oneparameter comprises a purge gas flow rate, and wherein the one or morecomputing devices is configured to cause a relatively high purge gasflow rate through the deposition delivery device.
 13. The system ofclaim 7, wherein the one or more computing devices is configured tocause the additive manufacturing system to perform the at least oneaction by at least placing the powder delivery device in a recoverystate while controlling the at least one operating parameter of theadditive manufacturing system.
 14. A method comprising: receiving, byone or more computing devices, image data representing illuminatedpowder of a powder stream between a powder delivery device of anadditive manufacturing system and a build surface of a component;determining, by the one or more computing devices, at least one metricassociated with the powder stream based on the received image data;determining, by the one or more computing devices, whether the at leastone metric indicates an abnormal state of the at least one metric; andcausing, by the one or more computing devices, the additivemanufacturing system to perform at least one action in response todetermining that the at least one metric indicates the abnormal state.15. The method of claim 14, wherein determining the at least one metriccomprises determining, by the one or more computing devices, a mass flowrate or powder distribution within the powder stream.
 16. The method ofclaim 15, wherein determining the at least one metric comprisesdetermining, by the one or more computing devices, a mass flow rate orpowder distribution for each region of interest of at least one regionof interest of the powder stream.
 17. The method of claim 15, whereindetermining the at least one metric comprises determining, by the one ormore computing devices, a radial powder distribution for each region ofinterest of at least one region of interest of the powder stream. 18.The method of claim 16, wherein determining whether the at least onemetric indicates an abnormal state comprises comparing, by the one ormore computing devices, the at least one metric associated with eachregion of interest to the at least one metric associated with each otherregion of interest and determining that the at least one metricindicates the abnormal state in response to the comparison showingdifferences between the metrics above a threshold difference value. 19.The method of claim 14, wherein determining whether the at least onemetric indicates the abnormal state of the at least one metric comprisescomparing, by the one or more computing devices, the at least one metricto a baseline range of values and determining that the at least onemetric indicates the abnormal state in response to the at least onemetric being outside of the baseline range of values.
 20. The method ofclaim 14, wherein causing the additive manufacturing system to performat least one action comprises controlling, by the one or more computingdevices, at least one operating parameter of the additive manufacturingsystem.